000			02278nam a22002057a 4500
005			20240508062721.0
008			240508b |||||||| |||| 00| 0 eng d
022			_a0022-0973
100			_aCox, Kyle
245			_aPower to Detect Moderated Effects in Studies with Three-Level Partially Nested Data _b(Journal Article)
260			_aPhiladelphia, USA _b: Taylor and Francis Group and Routledge _c,March 2024
300			_a130-153p.
440			_aThe Journal of Experimental Education _vVolume 92: Number 1, 2024
500			_a***______{For Hard Copy, Please visit Library.}________***
520			_aAbstract: Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a variety of experimental designs when moderation effects are of interest but has yet to establish power formulas for detecting moderation effects in three-level partially nested designs. To address this gap, we derive and assess the accuracy of power formulas for detecting the different types of moderation effects possible in these designs. Using Monte Carlo simulation studies, we probe power rates and adequate sample sizes for detecting the different moderation effects while varying common influential factors including variance in the outcome explained by covariates, magnitude of the moderation effect, and sample sizes. The power formulas developed improve the planning of experimental studies with partial nesting and encourage the inclusion of moderator variables to capture for whom and under what conditions a treatment is effective. Educational researchers also have some initial guidance regarding adequate sample sizes and the factors that influence detecting moderation effects in three-level partially nested designs.
650			_aCluster randomized trial| HLM| moderation effect| Monte Carlo Simulation| partially nested design| simulation studies| statistical power
700			_aKelcey, Ben | Luce, Hannah
856			_uhttps://doi.org/10.1080/00220973.2022.2141175
942			_cPER
999			_c45746 _d45745